This disclosure relates generally to pulse oximeters. More particularly, this disclosure relates to techniques for reducing power consumption in pulse oximeters, especially in battery operated pulse oximeter sensors. A pulse oximeter sensor here refers to a pulse oximeter unit provided with optical components, i.e. light emitting elements and one or more photodetectors, for collecting (photo)plethysmographic signal data. The sensor may be a single element or comprise a base unit and a separate optical unit that may be attached to a subject and connected to the base unit.
Pulse oximetry is a well-established technique for measuring oxygen saturation (SpO2) in arterial blood. SpO2 is an important parameter, nowadays often called as the fourth vital sign, which relates to the adequacy of oxygen supply to peripheral tissues and organs. Pulse oximeters provide instantaneous in-vivo measurements of arterial oxygenation, and thereby an early warning of arterial hypoxemia, for example. Pulse oximeters also display a photoplethysmographic (PPG) pulse waveform, which can be related to tissue blood volume and blood flow, i.e. the blood circulation, at the site of the measurement, typically in finger or ear.
At present, there is a growing interest to develop portable and wearable medical sensors for various medical applications that allow the subject to move freely and thus also remote supervision of the subject. Wireless Body Area Network (WBAN) refers to short-range radio-frequency communications technologies, which are specifically suited for transmitting measurement data between different patient-worn devices. In a typical set up, multiple tiny, battery-operated sensors (e.g. ECG patch on chest and SpO2 clip on finger) send measurement data to a patient-worn central unit. The central unit may be a small monitor by itself, including a display and even alarming functionality. The central unit may also communicate the measurement data and analysis results to a hospital-wide network using building-wide radio-frequency communications technologies, such as WiFi. Although WBAN technology is still in its infancy, WBAN applications are expected to increase drastically in the near future.
Low power consumption is a pre-requisite for WBAN sensors, and generally for all wearable or implanted sensors. As to pulse oximeters, the power consumption is largely due to the power requirement of the light sources (LEDs), which are normally driven continuously at a high rate. Therefore, techniques have been developed for reducing the power consumption of the LEDs. These techniques are based on reduction of the amplitude and/or width of the LED pulses, thereby to reduce the energy of the pulses. However, as the signal-to-noise ratio cannot be dropped below a certain threshold level, which may vary in different measurement environments, the reduction is normally accompanied with a noise measurement, so that the signal-to-noise ratio does not drop too low.
After today's advanced power reduction techniques have been taken into use, the power consumption of the pulse oximeter sensor is still around 20 mW. In a small finger clip type pulse oximeter sensor a suitable battery could be, for example, an LR44 coin cell. The voltage of such a battery is 1.5 V and the capacity 150 mAh, i.e. 220 mWh. That is, the battery provides about 10 hours of operating time with the above-mentioned power consumption. Consequently, the battery needs to be changed rather frequently, which is not only disturbing but may also cause a break in the measurement, especially in environments where the nursing staff is not constantly available for a battery change.
Lower power consumption levels have been reported in pulse oximeter sensors based on so-called compressed sensing. In these sensors, the plethysmographic signal data is acquired at a low sampling rate (i.e. LED blinking rate), which is below the Nyquist rate. This, however, increases the complexity of the signal processing needed to reconstruct the signal. Further, the more the sampling rate is below the Nyquist rate, the longer the signal sequence needed to reconstruct the signal. Consequently, the measurement slows down and an SpO2 value is not obtained for each cardiac cycle. Furthermore, reconstruction algorithms based on sub-Nyquist sampling are always based on assumptions about the amplitude and frequency content of the signal and noise. Hence, if the signal-to-noise ratio drops too low, this kind of reconstruction algorithms become unreliable.
Although the power consumption of a pulse oximeter sensor is largely due to the power requirement of the LEDs, the data transmission may also consume a considerable part of the power budget, at least if retransmissions are required frequently due to collisions, for example. It is generally thought that each sensor in a body area network samples and sends out data independently. In practice, it is, however, beneficial to synchronize the data transmission in order to minimize the number of collisions. For this purpose, a return data path is implemented. Hence, two-way communication and synchronization mechanisms are in place in body area networks. Data is typically sent in bursts with a typical interval of 50 to 1000 ms. Considering the power consumption, it is beneficial to increase the packet size, thereby to reduce the relative amount of overhead information to be transmitted. In case of signals with relatively high data rate, the data packet interval is usually short by nature. For example, for ECG measurement a packet interval of about 50 ms is appropriate, whereas temperature measurement data need not to be transmitted more frequently than about once in a second. As to pulse oximeters, the amount of data to be transmitted is normally rather small and thus the interval between data packets may be rather long.
Further, the development of pulse oximeters brings along new applications and higher performance. However, a pre-requisite for the introduction of new features and higher performance is an increased number of light sources in the pulse oximeter. When battery operability is required from the sensor, the power consumption issue is therefore even more essential in these new multi-wavelength pulse oximeters.
Consequently, in order to enhance the operating time of battery-operated pulse oximeter sensors and the fluency of continuous and long-term monitoring, it is desirable to provide pulse oximeter sensors that consume less power without compromising the quality and swiftness of the actual measurement and without adding complexity to the processing of the acquired plethysmographic signal data. Given the trend towards body area networks, it would also be beneficial if the power consumption of the pulse oximeter sensor could be reduced not only in terms of the LED operation but also in terms of the data transmission.